dfbetaPlots {car} | R Documentation |
These functions display index plots of dfbeta (effect on coefficients of deleting each observation in turn) and dfbetas (effect on coefficients of deleting each observation in turn, standardized by a deleted estimate of the coefficient standard error). In the plot of dfbeta, horizontal lines are drawn at 0 and +/- one standard error; in the plot of dfbetas, horizontal lines are drawn and 0 and +/- 1.
dfbetaPlots(model, ...) dfbetasPlots(model, ...) ## S3 method for class 'lm' dfbetaPlots(model, terms= ~ ., intercept=FALSE, layout=NULL, ask, main, xlab, ylab, labels=rownames(dfbeta), id.method="y", id.n=if(id.method[1]=="identify") Inf else 0, id.cex=1, id.col=palette()[1], col=palette()[1], grid=TRUE, ...) ## S3 method for class 'lm' dfbetasPlots(model, terms=~., intercept=FALSE, layout=NULL, ask, main, xlab, ylab, labels=rownames(dfbeta), id.method="y", id.n=if(id.method[1]=="identify") Inf else 0, id.cex=1, id.col=palette()[1], col=palette()[1], grid=TRUE, ...)
model |
model object produced by |
terms |
A one-sided formula that specifies a subset of the terms in the model.
One dfbeta or dfbetas plot is drawn for each regressor. The default
|
intercept |
Include the intercept in the plots; default is |
layout |
If set to a value like |
main |
The title of the graph; if missing, one will be supplied. |
xlab |
Horizontal axis label; defaults to |
ylab |
Vertical axis label; defaults to coefficient name. |
ask |
If |
... |
optional additional arguments to be passed to |
.
id.method,labels,id.n,id.cex,id.col |
Arguments for the labelling of
points. The default is |
col |
color for points; defaults to the first entry in the color |
grid |
If |
NULL
. These functions are used for their side effect: producing
plots.
John Fox jfox@mcmaster.ca, Sanford Weisberg sandy@umn.edu
Fox, J. (2008) Applied Regression Analysis and Generalized Linear Models, Second Edition. Sage.
Fox, J. and Weisberg, S. (2011) An R Companion to Applied Regression, Second Edition, Sage.
dfbetaPlots(lm(prestige ~ income + education + type, data=Duncan)) dfbetasPlots(glm(partic != "not.work" ~ hincome + children, data=Womenlf, family=binomial))